Triple

T31824151
Position Surface form Disambiguated ID Type / Status
Subject Skully E812345 entity
Predicate basedOn P98 FINISHED
Object Peter Pan franchise
The Peter Pan franchise is a collection of works across literature, film, theater, and other media centered on J.M. Barrie’s iconic character Peter Pan and the magical world of Neverland.
E673535 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Peter Pan franchise | Statement: [Skully, basedOn, Peter Pan franchise]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Peter Pan franchise
Triple: [Skully, basedOn, Peter Pan franchise]
Generated description
The Peter Pan franchise is a collection of works across literature, film, theater, and other media centered on J.M. Barrie’s iconic character Peter Pan and the magical world of Neverland.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f348e97fa48190aa06286962af6dee completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6af8130148190834cca27b2458735 completed May 3, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a212bc08190b6e37d3805fbd578 completed June 14, 2026, 11:01 a.m.
NEDg Description generation batch_6a2e8a9962b08190bb680bf5e01bba5a completed June 14, 2026, 11:03 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8b16d14c8190917632abbb0f601e completed June 14, 2026, 11:05 a.m.
Created at: April 30, 2026, 11:46 p.m.